‘Judicial treatment of ouster clauses: time for a new approach?’
Bibliographic record
Abstract
This thesis aims to assess whether the current judicial approach to ouster clauses in the United Kingdom is fit for purpose, and if not, what aspects should form part of a future approach. After finding the current Anisminic derived approach to be deficient, the rest of the thesis is dedicated to exploring the case for a new approach aided by comparative study of judicial review in Australia, Canada and the United States of America. The approach to ouster clauses proposed by this thesis is multifaceted, reflecting the fact that ouster clauses do not seek to exclude a single type of decision or decisionmakers from judicial review. It is concluded that the extent to which an ouster clause is effective should depend on contextual rule of law based considerations, and on the core notion that Parliament is conceptually limited from fully ousting judicial review.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.025 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.022 |
| Scholarly communication | 0.012 | 0.014 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.008 | 0.012 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".